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Record W7061202716

Potential solutions to Manitoba’s high school dropout crisis: insights of a high school classroom teacher think tank

2014· dissertation· en· W7061202716 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2014
Typedissertation
Languageen
FieldEngineering
TopicMagnetic Field Sensors Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSchool dropoutInterpretation (philosophy)Dropout (neural networks)School teachersCritical thinking
DOInot available

Abstract

fetched live from OpenAlex

It is a widespread belief in western society today that every adolescent is capable of attaining a high school diploma (Pharris-Ciureja, Hirschman, & Willhoft, 2012). In reality, a Statistics Canada (2012) “Labour Force Survey” concluded that only 73.9% of all 18 and 19 year olds have received high school diplomas. Richards (2009) stated that Manitoba’s high school dropout rate is the highest in Canada, and is twice as high as that of British Columbia. Unfortunately, many adolescents have started on the path to dropping out long before they enter high school (Downing & Peckham-Hardin, 2007) due to a combination of sociological, socioeconomic, cultural, developmental, behavioural, and academic factors (Englund, Edgeland, & Collins, 2008; Pharris-Ciureja, Hirschman, & Willhoft, 2012; Richards 2009). To better understand this phenomenon, I used the critical analytical tool of the immanent critique (Skrtic, 1995); and several different critical thinking tools (Levy, 2010). I also reviewed literature concerning sociology and education, Manitoba’s interpretation of inclusion, and the unique nature of high schools and their teachers. The purpose of this study was to invite Manitoba high school classroom teachers into a think tank and ask them what they believe they do to help adolescents stay in school and graduate. I found that the high school classroom teachers who participated in the study creatively strived to connect with students, worked individually and collaboratively with colleagues, and acknowledged the need for legislation, policies, and administration. They also took the time to examine current educational practices and continuously searched for innovative ways to improve their classrooms, schools, and the system-at-large. I concluded that school systems would greatly benefit from seeking out the voices of high school teachers and asking them what they think.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.187
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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